Pricing of weather index insurance premium using Black Scholes framework for smallholder farmers in Burundi

Abstract

Agriculture plays a critical role in Burundi’s economy, with smallholder farmers constituting the majority of the agricultural workforce. However, reliance on rain-fed farming exposes these farmers to climate-related risks, such as erratic rainfall and prolonged droughts, leading to significant crop yield losses. Traditional crop insurance models are often inaccessible due to high costs and administrative complexities. This study explores an innovative approach by applying the Black-Scholes model to price weather index insurance premiums, offering a cost effective and efficient alternative. The research hypothesizes that the Black-Scholes framework can be adapted to accurately determine insurance premiums based on historical weather and crop yield data. A quantitative research design is employed, utilizing secondary data on rainfall patterns and maize yields in Burundi spanning 32 years (1991–2022). Correlation analysis confirms a strong relationship between rainfall variability and maize production, justifying the use of rainfall as an index for insurance pricing. Lognormality tests validate the suitability of the Black-Scholes model for this application. The results indicate that insurance premiums fluctuate based on the chosen rainfall thresholds, with higher thresholds reducing payout probabilities and lowering premium costs. The study highlights the model’s potential for improving financial resilience among smallholder farmers while addressing affordability concerns through policy recommendations such as government subsidies and public-private partnerships. Future research should explore region-specific data and extreme climate event simulations to enhance precision. The findings provide a robust foundation for expanding weather index insurance in Burundi, ultimately contributing to agricultural sustainability and economic stability.